Papers with Code 아카이브
Pedestrian Detection
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 1
- 평가표
- 9
- 보존된 평가 기록
- 92
Pedestrian detection is the task of detecting pedestrians from a camera.
Further state-of-the-art results (e.g. on the KITTI dataset) can be found at 3D Object Detection.
<span style="color:grey; opacity: 0.6">( Image credit: High-level Semantic Feature Detection: A New Perspective for Pedestrian Detection )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Smiler-Jin/Yolov4
https://github.com/SoonminHwang/rgbt-ped-detection
https://github.com/Spain2394/darknet
https://github.com/SpanoChristian/darknet
https://github.com/Stephenfang51/Focal_loss_turtorial
https://github.com/Suci2609/generate_train_list.py-
https://github.com/Sujith2k/darknet
https://github.com/Sushma07/dancedarknet
https://github.com/TamirShasha/Mars_yolo
https://github.com/Techyee/darknet_resource
https://github.com/Thinklab-SJTU/CSL_RetinaNet_Tensorflow
https://github.com/Tony363/Teamplay_Yolov3
https://github.com/TravisTorch/Pytorch
https://github.com/TusharMhaske28/Object-Detection
https://github.com/TusharMhaske28/Thermal-Object
https://github.com/TusharMhaske28/summer-project
https://github.com/VideoObjectSearch/ALFNet
https://github.com/Vijayabhaskar96/Object-Detection-Algorithms
https://github.com/ViswanathaReddyGajjala/EfficientNet-RetinaNet
https://github.com/Viveksbawa/SARAS-ESAD-Baseline
https://github.com/WangMian-Maker/Flask
https://github.com/WangWenhao0716/Adapted-Center-and-Scale-Prediction
Adapted Center and Scale Prediction: More Stable and More Accurate
https://github.com/Wangxy2180/darknetKinectDetect
https://github.com/WongKinYiu/YOLO
YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
https://github.com/XiaoMi/mace
https://github.com/XuanjieXiao/vehicle-detection-by-using-camera
https://github.com/YCHung1998/Object-Detection
https://github.com/YIZHE12/fashiontags
https://github.com/YIZHE12/robots
https://github.com/Yamahitsuji/darknet
https://github.com/Yashgh7076/Eluvio-ML-Scene-Segmentation
https://github.com/Yonder-OSS/D3M-Primitives
https://github.com/YudeWang/UNet-Satellite-Image-Segmentation
https://github.com/YunYang1994/tensorflow-yolov3
https://github.com/Yuxiang1995/ICDAR2021_MFD
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.